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1. Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Author

Itziar de Rojas, Sonia Moreno-Grau, Niccolo Tesi, Benjamin Grenier-Boley, Victor Andrade, Iris E. Jansen, Nancy L. Pedersen, Najada Stringa, Anna Zettergren, Isabel Hernández, Laura Montrreal, Carmen Antúnez, Anna Antonell, Rick M. Tankard, Joshua C. Bis, Rebecca Sims, Céline Bellenguez, Inés Quintela, Antonio González-Perez, Miguel Calero, Emilio Franco-Macías, Juan Macías, Rafael Blesa, Laura Cervera-Carles, Manuel Menéndez-González, Ana Frank-García, Jose Luís Royo, Fermin Moreno, Raquel Huerto Vilas, Miquel Baquero, Mónica Diez-Fairen, Carmen Lage, Sebastián García-Madrona, Pablo García-González, Emilio Alarcón-Martín, Sergi Valero, Oscar Sotolongo-Grau, Abbe Ullgren, Adam C. Naj, Afina W. Lemstra, Alba Benaque, Alba Pérez-Cordón, Alberto Benussi, Alberto Rábano, Alessandro Padovani, Alessio Squassina, Alexandre de Mendonça, Alfonso Arias Pastor, Almar A. L. Kok, Alun Meggy, Ana Belén Pastor, Ana Espinosa, Anaïs Corma-Gómez, Angel Martín Montes, Ángela Sanabria, Anita L. DeStefano, Anja Schneider, Annakaisa Haapasalo, Anne Kinhult Ståhlbom, Anne Tybjærg-Hansen, Annette M. Hartmann, Annika Spottke, Arturo Corbatón-Anchuelo, Arvid Rongve, Barbara Borroni, Beatrice Arosio, Benedetta Nacmias, Børge G. Nordestgaard, Brian W. Kunkle, Camille Charbonnier, Carla Abdelnour, Carlo Masullo, Carmen Martínez Rodríguez, Carmen Muñoz-Fernandez, Carole Dufouil, Caroline Graff, Catarina B. Ferreira, Caterina Chillotti, Chandra A. Reynolds, Chiara Fenoglio, Christine Van Broeckhoven, Christopher Clark, Claudia Pisanu, Claudia L. Satizabal, Clive Holmes, Dolores Buiza-Rueda, Dag Aarsland, Dan Rujescu, Daniel Alcolea, Daniela Galimberti, David Wallon, Davide Seripa, Edna Grünblatt, Efthimios Dardiotis, Emrah Düzel, Elio Scarpini, Elisa Conti, Elisa Rubino, Ellen Gelpi, Eloy Rodriguez-Rodriguez, Emmanuelle Duron, Eric Boerwinkle, Evelyn Ferri, Fabrizio Tagliavini, Fahri Küçükali, Florence Pasquier, Florentino Sanchez-Garcia, Francesca Mangialasche, Frank Jessen, Gaël Nicolas, Geir Selbæk, Gemma Ortega, Geneviève Chêne, Georgios Hadjigeorgiou, Giacomina Rossi, Gianfranco Spalletta, Giorgio Giaccone, Giulia Grande, Giuliano Binetti, Goran Papenberg, Harald Hampel, Henri Bailly, Henrik Zetterberg, Hilkka Soininen, Ida K. Karlsson, Ignacio Alvarez, Ildebrando Appollonio, Ina Giegling, Ingmar Skoog, Ingvild Saltvedt, Innocenzo Rainero, Irene Rosas Allende, Jakub Hort, Janine Diehl-Schmid, Jasper Van Dongen, Jean-Sebastien Vidal, Jenni Lehtisalo, Jens Wiltfang, Jesper Qvist Thomassen, Johannes Kornhuber, Jonathan L. Haines, Jonathan Vogelgsang, Juan A. Pineda, Juan Fortea, Julius Popp, Jürgen Deckert, Katharina Buerger, Kevin Morgan, Klaus Fließbach, Kristel Sleegers, Laura Molina-Porcel, Lena Kilander, Leonie Weinhold, Lindsay A. Farrer, Li-San Wang, Luca Kleineidam, Lucia Farotti, Lucilla Parnetti, Lucio Tremolizzo, Lucrezia Hausner, Luisa Benussi, Lutz Froelich, M. Arfan Ikram, M. Candida Deniz-Naranjo, Magda Tsolaki, Maitée Rosende-Roca, Malin Löwenmark, Marc Hulsman, Marco Spallazzi, Margaret A. Pericak-Vance, Margaret Esiri, María Bernal Sánchez-Arjona, Maria Carolina Dalmasso, María Teresa Martínez-Larrad, Marina Arcaro, Markus M. Nöthen, Marta Fernández-Fuertes, Martin Dichgans, Martin Ingelsson, Martin J. Herrmann, Martin Scherer, Martin Vyhnalek, Mary H. Kosmidis, Mary Yannakoulia, Matthias Schmid, Michael Ewers, Michael T. Heneka, Michael Wagner, Michela Scamosci, Miia Kivipelto, Mikko Hiltunen, Miren Zulaica, Montserrat Alegret, Myriam Fornage, Natalia Roberto, Natasja M. van Schoor, Nazib M. Seidu, Nerisa Banaj, Nicola J. Armstrong, Nikolaos Scarmeas, Norbert Scherbaum, Oliver Goldhardt, Oliver Hanon, Oliver Peters, Olivia Anna Skrobot, Olivier Quenez, Ondrej Lerch, Paola Bossù, Paolo Caffarra, Paolo Dionigi Rossi, Paraskevi Sakka, Per Hoffmann, Peter A. Holmans, Peter Fischer, Peter Riederer, Qiong Yang, Rachel Marshall, Rajesh N. Kalaria, Richard Mayeux, Rik Vandenberghe, Roberta Cecchetti, Roberta Ghidoni, Ruth Frikke-Schmidt, Sandro Sorbi, Sara Hägg, Sebastiaan Engelborghs, Seppo Helisalmi, Sigrid Botne Sando, Silke Kern, Silvana Archetti, Silvia Boschi, Silvia Fostinelli, Silvia Gil, Silvia Mendoza, Simon Mead, Simona Ciccone, Srdjan Djurovic, Stefanie Heilmann-Heimbach, Steffi Riedel-Heller, Teemu Kuulasmaa, Teodoro del Ser, Thibaud Lebouvier, Thomas Polak, Tiia Ngandu, Timo Grimmer, Valentina Bessi, Valentina Escott-Price, Vilmantas Giedraitis, Vincent Deramecourt, Wolfgang Maier, Xueqiu Jian, Yolande A. L. Pijnenburg, EADB contributors, DEGESCO consortium, IGAP (ADGC, CHARGE, EADI, GERAD), PGC-ALZ consortia, Patrick Gavin Kehoe, Guillermo Garcia-Ribas, Pascual Sánchez-Juan, Pau Pastor, Jordi Pérez-Tur, Gerard Piñol-Ripoll, Adolfo Lopez de Munain, Jose María García-Alberca, María J. Bullido, Victoria Álvarez, Alberto Lleó, Luis M. Real, Pablo Mir, Miguel Medina, Philip Scheltens, Henne Holstege, Marta Marquié, María Eugenia Sáez, Ángel Carracedo, Philippe Amouyel, Gerard D. Schellenberg, Julie Williams, Sudha Seshadri, Cornelia M. van Duijn, Karen A. Mather, Raquel Sánchez-Valle, Manuel Serrano-Ríos, Adelina Orellana, Lluís Tárraga, Kaj Blennow, Martijn Huisman, Ole A. Andreassen, Danielle Posthuma, Jordi Clarimón, Mercè Boada, Wiesje M. van der Flier, Alfredo Ramirez, Jean-Charles Lambert, Sven J. van der Lee, and Agustín Ruiz

Subjects
Science
Abstract

Known genetic loci account for only a fraction of the genetic contribution to Alzheimer’s disease. Here, the authors have performed a large genome-wide meta-analysis comprising 409,435 individuals to discover 6 new loci and demonstrate the efficacy of an Alzheimer’s disease polygenic risk score.

Published
2021
Full Text
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2. Author Correction: Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Author

Itziar de Rojas, Sonia Moreno-Grau, Niccolo Tesi, Benjamin Grenier-Boley, Victor Andrade, Iris E. Jansen, Nancy L. Pedersen, Najada Stringa, Anna Zettergren, Isabel Hernández, Laura Montrreal, Carmen Antúnez, Anna Antonell, Rick M. Tankard, Joshua C. Bis, Rebecca Sims, Céline Bellenguez, Inés Quintela, Antonio González-Perez, Miguel Calero, Emilio Franco-Macías, Juan Macías, Rafael Blesa, Laura Cervera-Carles, Manuel Menéndez-González, Ana Frank-García, Jose Luís Royo, Fermin Moreno, Raquel Huerto Vilas, Miquel Baquero, Mónica Diez-Fairen, Carmen Lage, Sebastián García-Madrona, Pablo García-González, Emilio Alarcón-Martín, Sergi Valero, Oscar Sotolongo-Grau, Abbe Ullgren, Adam C. Naj, Afina W. Lemstra, Alba Benaque, Alba Pérez-Cordón, Alberto Benussi, Alberto Rábano, Alessandro Padovani, Alessio Squassina, Alexandre de Mendonça, Alfonso Arias Pastor, Almar A. L. Kok, Alun Meggy, Ana Belén Pastor, Ana Espinosa, Anaïs Corma-Gómez, Angel Martín Montes, Ángela Sanabria, Anita L. DeStefano, Anja Schneider, Annakaisa Haapasalo, Anne Kinhult Ståhlbom, Anne Tybjærg-Hansen, Annette M. Hartmann, Annika Spottke, Arturo Corbatón-Anchuelo, Arvid Rongve, Barbara Borroni, Beatrice Arosio, Benedetta Nacmias, Børge G. Nordestgaard, Brian W. Kunkle, Camille Charbonnier, Carla Abdelnour, Carlo Masullo, Carmen Martínez Rodríguez, Carmen Muñoz-Fernandez, Carole Dufouil, Caroline Graff, Catarina B. Ferreira, Caterina Chillotti, Chandra A. Reynolds, Chiara Fenoglio, Christine Van Broeckhoven, Christopher Clark, Claudia Pisanu, Claudia L. Satizabal, Clive Holmes, Dolores Buiza-Rueda, Dag Aarsland, Dan Rujescu, Daniel Alcolea, Daniela Galimberti, David Wallon, Davide Seripa, Edna Grünblatt, Efthimios Dardiotis, Emrah Düzel, Elio Scarpini, Elisa Conti, Elisa Rubino, Ellen Gelpi, Eloy Rodriguez-Rodriguez, Emmanuelle Duron, Eric Boerwinkle, Evelyn Ferri, Fabrizio Tagliavini, Fahri Küçükali, Florence Pasquier, Florentino Sanchez-Garcia, Francesca Mangialasche, Frank Jessen, Gaël Nicolas, Geir Selbæk, Gemma Ortega, Geneviève Chêne, Georgios Hadjigeorgiou, Giacomina Rossi, Gianfranco Spalletta, Giorgio Giaccone, Giulia Grande, Giuliano Binetti, Goran Papenberg, Harald Hampel, Henri Bailly, Henrik Zetterberg, Hilkka Soininen, Ida K. Karlsson, Ignacio Alvarez, Ildebrando Appollonio, Ina Giegling, Ingmar Skoog, Ingvild Saltvedt, Innocenzo Rainero, Irene Rosas Allende, Jakub Hort, Janine Diehl-Schmid, Jasper Van Dongen, Jean-Sebastien Vidal, Jenni Lehtisalo, Jens Wiltfang, Jesper Qvist Thomassen, Johannes Kornhuber, Jonathan L. Haines, Jonathan Vogelgsang, Juan A. Pineda, Juan Fortea, Julius Popp, Jürgen Deckert, Katharina Buerger, Kevin Morgan, Klaus Fließbach, Kristel Sleegers, Laura Molina-Porcel, Lena Kilander, Leonie Weinhold, Lindsay A. Farrer, Li-San Wang, Luca Kleineidam, Lucia Farotti, Lucilla Parnetti, Lucio Tremolizzo, Lucrezia Hausner, Luisa Benussi, Lutz Froelich, M. Arfan Ikram, M. Candida Deniz-Naranjo, Magda Tsolaki, Maitée Rosende-Roca, Malin Löwenmark, Marc Hulsman, Marco Spallazzi, Margaret A. Pericak-Vance, Margaret Esiri, María Bernal Sánchez-Arjona, Maria Carolina Dalmasso, María Teresa Martínez-Larrad, Marina Arcaro, Markus M. Nöthen, Marta Fernández-Fuertes, Martin Dichgans, Martin Ingelsson, Martin J. Herrmann, Martin Scherer, Martin Vyhnalek, Mary H. Kosmidis, Mary Yannakoulia, Matthias Schmid, Michael Ewers, Michael T. Heneka, Michael Wagner, Michela Scamosci, Miia Kivipelto, Mikko Hiltunen, Miren Zulaica, Montserrat Alegret, Myriam Fornage, Natalia Roberto, Natasja M. van Schoor, Nazib M. Seidu, Nerisa Banaj, Nicola J. Armstrong, Nikolaos Scarmeas, Norbert Scherbaum, Oliver Goldhardt, Oliver Hanon, Oliver Peters, Olivia Anna Skrobot, Olivier Quenez, Ondrej Lerch, Paola Bossù, Paolo Caffarra, Paolo Dionigi Rossi, Paraskevi Sakka, Patrizia Mecocci, Per Hoffmann, Peter A. Holmans, Peter Fischer, Peter Riederer, Qiong Yang, Rachel Marshall, Rajesh N. Kalaria, Richard Mayeux, Rik Vandenberghe, Roberta Cecchetti, Roberta Ghidoni, Ruth Frikke-Schmidt, Sandro Sorbi, Sara Hägg, Sebastiaan Engelborghs, Seppo Helisalmi, Sigrid Botne Sando, Silke Kern, Silvana Archetti, Silvia Boschi, Silvia Fostinelli, Silvia Gil, Silvia Mendoza, Simon Mead, Simona Ciccone, Srdjan Djurovic, Stefanie Heilmann-Heimbach, Steffi Riedel-Heller, Teemu Kuulasmaa, Teodoro del Ser, Thibaud Lebouvier, Thomas Polak, Tiia Ngandu, Timo Grimmer, Valentina Bessi, Valentina Escott-Price, Vilmantas Giedraitis, Vincent Deramecourt, Wolfgang Maier, Xueqiu Jian, Yolande A. L. Pijnenburg, EADB contributors, DEGESCO consortium, IGAP (ADGC, CHARGE, EADI, GERAD), PGC-ALZ consortia, Patrick Gavin Kehoe, Guillermo Garcia-Ribas, Pascual Sánchez-Juan, Pau Pastor, Jordi Pérez-Tur, Gerard Piñol-Ripoll, Adolfo Lopez de Munain, Jose María García-Alberca, María J. Bullido, Victoria Álvarez, Alberto Lleó, Luis M. Real, Pablo Mir, Miguel Medina, Philip Scheltens, Henne Holstege, Marta Marquié, María Eugenia Sáez, Ángel Carracedo, Philippe Amouyel, Gerard D. Schellenberg, Julie Williams, Sudha Seshadri, Cornelia M. van Duijn, Karen A. Mather, Raquel Sánchez-Valle, Manuel Serrano-Ríos, Adelina Orellana, Lluís Tárraga, Kaj Blennow, Martijn Huisman, Ole A. Andreassen, Danielle Posthuma, Jordi Clarimón, Mercè Boada, Wiesje M. van der Flier, Alfredo Ramirez, Jean-Charles Lambert, Sven J. van der Lee, and Agustín Ruiz

Subjects
Science
Published
2023
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3. Automated identification of clinical features from sparsely annotated 3-dimensional medical imaging

Author

Nadav Rakocz, Jeffrey N. Chiang, Muneeswar G. Nittala, Giulia Corradetti, Liran Tiosano, Swetha Velaga, Michael Thompson, Brian L. Hill, Sriram Sankararaman, Jonathan L. Haines, Margaret A. Pericak-Vance, Dwight Stambolian, Srinivas R. Sadda, and Eran Halperin

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Abstract One of the core challenges in applying machine learning and artificial intelligence to medicine is the limited availability of annotated medical data. Unlike in other applications of machine learning, where an abundance of labeled data is available, the labeling and annotation of medical data and images require a major effort of manual work by expert clinicians who do not have the time to annotate manually. In this work, we propose a new deep learning technique (SLIVER-net), to predict clinical features from 3-dimensional volumes using a limited number of manually annotated examples. SLIVER-net is based on transfer learning, where we borrow information about the structure and parameters of the network from publicly available large datasets. Since public volume data are scarce, we use 2D images and account for the 3-dimensional structure using a novel deep learning method which tiles the volume scans, and then adds layers that leverage the 3D structure. In order to illustrate its utility, we apply SLIVER-net to predict risk factors for progression of age-related macular degeneration (AMD), a leading cause of blindness, from optical coherence tomography (OCT) volumes acquired from multiple sites. SLIVER-net successfully predicts these factors despite being trained with a relatively small number of annotated volumes (hundreds) and only dozens of positive training examples. Our empirical evaluation demonstrates that SLIVER-net significantly outperforms standard state-of-the-art deep learning techniques used for medical volumes, and its performance is generalizable as it was validated on an external testing set. In a direct comparison with a clinician panel, we find that SLIVER-net also outperforms junior specialists, and identifies AMD progression risk factors similarly to expert retina specialists.

Published
2021
Full Text
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4. Genome-wide meta-analysis identifies 127 open-angle glaucoma loci with consistent effect across ancestries

Author

Puya Gharahkhani, Eric Jorgenson, Pirro Hysi, Anthony P. Khawaja, Sarah Pendergrass, Xikun Han, Jue Sheng Ong, Alex W. Hewitt, Ayellet V. Segrè, John M. Rouhana, Andrew R. Hamel, Robert P. Igo, Helene Choquet, Ayub Qassim, Navya S. Josyula, Jessica N. Cooke Bailey, Pieter W. M. Bonnemaijer, Adriana Iglesias, Owen M. Siggs, Terri L. Young, Veronique Vitart, Alberta A. H. J. Thiadens, Juha Karjalainen, Steffen Uebe, Ronald B. Melles, K. Saidas Nair, Robert Luben, Mark Simcoe, Nishani Amersinghe, Angela J. Cree, Rene Hohn, Alicia Poplawski, Li Jia Chen, Shi-Song Rong, Tin Aung, Eranga Nishanthie Vithana, NEIGHBORHOOD consortium, ANZRAG consortium, Biobank Japan project, FinnGen study, UK Biobank Eye and Vision Consortium, GIGA study group, and Me Research Team, Gen Tamiya, Yukihiro Shiga, Masayuki Yamamoto, Toru Nakazawa, Hannah Currant, Ewan Birney, Xin Wang, Adam Auton, Michelle K. Lupton, Nicholas G. Martin, Adeyinka Ashaye, Olusola Olawoye, Susan E. Williams, Stephen Akafo, Michele Ramsay, Kazuki Hashimoto, Yoichiro Kamatani, Masato Akiyama, Yukihide Momozawa, Paul J. Foster, Peng T. Khaw, James E. Morgan, Nicholas G. Strouthidis, Peter Kraft, Jae H. Kang, Chi Pui Pang, Francesca Pasutto, Paul Mitchell, Andrew J. Lotery, Aarno Palotie, Cornelia van Duijn, Jonathan L. Haines, Chris Hammond, Louis R. Pasquale, Caroline C. W. Klaver, Michael Hauser, Chiea Chuen Khor, David A. Mackey, Michiaki Kubo, Ching-Yu Cheng, Jamie E. Craig, Stuart MacGregor, and Janey L. Wiggs

Subjects
Science
Abstract

Primary open-angle glaucoma (POAG) is highly heritable, yet not well understood from a genetic perspective. Here, the authors perform a meta-analysis of genome-wide association studies in 34,179 POAG cases, identifying 44 previously unreported risk loci and mapping effects across multiple ethnicities.

Published
2021
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5. Exceptionally low likelihood of Alzheimer’s dementia in APOE2 homozygotes from a 5,000-person neuropathological study

Author

Eric M. Reiman, Joseph F. Arboleda-Velasquez, Yakeel T. Quiroz, Matthew J. Huentelman, Thomas G. Beach, Richard J. Caselli, Yinghua Chen, Yi Su, Amanda J. Myers, John Hardy, Jean Paul Vonsattel, Steven G. Younkin, David A. Bennett, Philip L. De Jager, Eric B. Larson, Paul K. Crane, C. Dirk Keene, M. Ilyas Kamboh, Julia K. Kofler, Linda Duque, John R. Gilbert, Harry E. Gwirtsman, Joseph D. Buxbaum, Dennis W. Dickson, Matthew P. Frosch, Bernardino F. Ghetti, Kathryn L. Lunetta, Li-San Wang, Bradley T. Hyman, Walter A. Kukull, Tatiana Foroud, Jonathan L. Haines, Richard P. Mayeux, Margaret A. Pericak-Vance, Julie A. Schneider, John Q. Trojanowski, Lindsay A. Farrer, Gerard D. Schellenberg, Gary W. Beecham, Thomas J. Montine, Gyungah R. Jun, and The Alzheimer’s Disease Genetics Consortium

Subjects
Science
Abstract

APOE is the major genetic risk factor for Alzheimer’s disease. In a large number of neuropathologically confirmed cases and controls, the impact of different APOE genotypes on Alzheimer’s dementia risk was greater than previously thought and APOE2 homozygotes had an exceptionally low risk.

Published
2020
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6. Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases

Author

Adriana I. Iglesias, Aniket Mishra, Veronique Vitart, Yelena Bykhovskaya, René Höhn, Henriët Springelkamp, Gabriel Cuellar-Partida, Puya Gharahkhani, Jessica N. Cooke Bailey, Colin E. Willoughby, Xiaohui Li, Seyhan Yazar, Abhishek Nag, Anthony P. Khawaja, Ozren Polašek, David Siscovick, Paul Mitchell, Yih Chung Tham, Jonathan L. Haines, Lisa S. Kearns, Caroline Hayward, Yuan Shi, Elisabeth M. van Leeuwen, Kent D. Taylor, Blue Mountains Eye Study—GWAS group, Pieter Bonnemaijer, Jerome I. Rotter, Nicholas G. Martin, Tanja Zeller, Richard A. Mills, Emmanuelle Souzeau, Sandra E. Staffieri, Jost B. Jonas, Irene Schmidtmann, Thibaud Boutin, Jae H. Kang, Sionne E. M. Lucas, Tien Yin Wong, Manfred E. Beutel, James F. Wilson, NEIGHBORHOOD Consortium, Wellcome Trust Case Control Consortium 2 (WTCCC2), André G. Uitterlinden, Eranga N. Vithana, Paul J. Foster, Pirro G. Hysi, Alex W. Hewitt, Chiea Chuen Khor, Louis R. Pasquale, Grant W. Montgomery, Caroline C. W. Klaver, Tin Aung, Norbert Pfeiffer, David A. Mackey, Christopher J. Hammond, Ching-Yu Cheng, Jamie E. Craig, Yaron S. Rabinowitz, Janey L. Wiggs, Kathryn P. Burdon, Cornelia M. van Duijn, and Stuart MacGregor

Subjects
Science
Abstract

Reduced central corneal thickness (CCT) is observed in common eye diseases as well as in rare Mendelian disorders. Here, in a cross-ancestry GWAS, the authors identify 19 novel genetic loci associated with CCT, a subset of which is involved in rare corneal or connective tissue disorders.

Published
2018
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7. Author Correction: Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases

Author

Adriana I. Iglesias, Aniket Mishra, Veronique Vitart, Yelena Bykhovskaya, René Höhn, Henriët Springelkamp, Gabriel Cuellar-Partida, Puya Gharahkhani, Jessica N. Cooke Bailey, Colin E. Willoughby, Xiaohui Li, Seyhan Yazar, Abhishek Nag, Anthony P. Khawaja, Ozren Polašek, David Siscovick, Paul Mitchell, Yih Chung Tham, Jonathan L. Haines, Lisa S. Kearns, Caroline Hayward, Yuan Shi, Elisabeth M. van Leeuwen, Kent D. Taylor, Blue Mountains Eye Study - GWAS group, Pieter Bonnemaijer, Jerome I. Rotter, Nicholas G. Martin, Tanja Zeller, Richard A. Mills, Emmanuelle Souzeau, Sandra E. Staffieri, Jost B. Jonas, Irene Schmidtmann, Thibaud Boutin, Jae H. Kang, Sionne E. M. Lucas, Tien Yin Wong, Manfred E. Beutel, James F. Wilson, Wellcome Trust Case Control Consortium 2 (WTCCC2), NEIGHBORHOOD consortium, André G. Uitterlinden, Eranga N. Vithana, Paul J. Foster, Pirro G. Hysi, Alex W. Hewitt, Chiea Chuen Khor, Louis R. Pasquale, Grant W. Montgomery, Caroline C. W. Klaver, Tin Aung, Norbert Pfeiffer, David A. Mackey, Christopher J. Hammond, Ching-Yu Cheng, Jamie E. Craig, Yaron S. Rabinowitz, Janey L. Wiggs, Kathryn P. Burdon, Cornelia M. van Duijn, and Stuart MacGregor

Subjects
Science
Abstract

Emmanuelle Souzeau, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this Article. This has now been corrected in both the PDF and HTML versions of the Article.

Published
2019
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8. A population-specific reference panel empowers genetic studies of Anabaptist populations

Author

Liping Hou, Rachel L. Kember, Jared C. Roach, Jeffrey R. O’Connell, David W. Craig, Maja Bucan, William K. Scott, Margaret Pericak-Vance, Jonathan L. Haines, Michael H. Crawford, Alan R. Shuldiner, and Francis J. McMahon

Subjects
Medicine, Science
Abstract

Abstract Genotype imputation is a powerful strategy for achieving the large sample sizes required for identification of variants underlying complex phenotypes, but imputation of rare variants remains problematic. Genetically isolated populations offer one solution, however population-specific reference panels are needed to assure optimal imputation accuracy and allele frequency estimation. Here we report the Anabaptist Genome Reference Panel (AGRP), the first whole-genome catalogue of variants and phased haplotypes in people of Amish and Mennonite ancestry. Based on high-depth whole-genome sequence (WGS) from 265 individuals, the AGRP contains >12 M high-confidence single nucleotide variants and short indels, of which ~12.5% are novel. These Anabaptist-specific variants were more deleterious than variants with comparable frequencies observed in the 1000 Genomes panel. About 43,000 variants showed enriched allele frequencies in AGRP, consistent with drift. When combined with the 1000 Genomes Project reference panel, the AGRP substantially improved imputation, especially for rarer variants. The AGRP is freely available to researchers through an imputation server.

Published
2017
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9. Automated identification of clinical features from sparsely annotated 3-dimensional medical imaging

Author

Srinivas R. Sadda, Nadav Rakocz, Margaret A. Pericak-Vance, Liran Tiosano, Swetha Bindu Velaga, Jeffrey N. Chiang, Sriram Sankararaman, Dwight Stambolian, Michael Thompson, Eran Halperin, Giulia Corradetti, Jonathan L. Haines, Muneeswar Gupta Nittala, and Brian L. Hill

Subjects
Computer science, Computer applications to medicine. Medical informatics, R858-859.7, Medicine (miscellaneous), Bioengineering, Health Informatics, Neurodegenerative, Machine learning, computer.software_genre, Article, Set (abstract data type), Macular Degeneration, 03 medical and health sciences, Annotation, 0302 clinical medicine, Health Information Management, Medical imaging, Leverage (statistics), Eye manifestations, Eye Disease and Disorders of Vision, business.industry, Deep learning, Volume (computing), Computer Science Applications, Identification (information), Three-dimensional imaging, 030221 ophthalmology & optometry, Biomedical Imaging, Artificial intelligence, business, Transfer of learning, computer, Biomarkers, 030217 neurology & neurosurgery
Abstract

One of the core challenges in applying machine learning and artificial intelligence to medicine is the limited availability of annotated medical data. Unlike in other applications of machine learning, where an abundance of labeled data is available, the labeling and annotation of medical data and images require a major effort of manual work by expert clinicians who do not have the time to annotate manually. In this work, we propose a new deep learning technique (SLIVER-net), to predict clinical features from 3-dimensional volumes using a limited number of manually annotated examples. SLIVER-net is based on transfer learning, where we borrow information about the structure and parameters of the network from publicly available large datasets. Since public volume data are scarce, we use 2D images and account for the 3-dimensional structure using a novel deep learning method which tiles the volume scans, and then adds layers that leverage the 3D structure. In order to illustrate its utility, we apply SLIVER-net to predict risk factors for progression of age-related macular degeneration (AMD), a leading cause of blindness, from optical coherence tomography (OCT) volumes acquired from multiple sites. SLIVER-net successfully predicts these factors despite being trained with a relatively small number of annotated volumes (hundreds) and only dozens of positive training examples. Our empirical evaluation demonstrates that SLIVER-net significantly outperforms standard state-of-the-art deep learning techniques used for medical volumes, and its performance is generalizable as it was validated on an external testing set. In a direct comparison with a clinician panel, we find that SLIVER-net also outperforms junior specialists, and identifies AMD progression risk factors similarly to expert retina specialists.

Published
2021

10. A population-specific reference panel empowers genetic studies of Anabaptist populations

Author

Jared C. Roach, Jeffrey R. O'Connell, William K. Scott, Maja Bucan, Jonathan L. Haines, Francis J. McMahon, Liping Hou, Rachel L. Kember, Alan R. Shuldiner, Margaret A. Pericak-Vance, Michael H. Crawford, and David Craig

Subjects
0301 basic medicine, Genetics, Multidisciplinary, Science, Haplotype, digestive, oral, and skin physiology, 030105 genetics & heredity, Biology, Genome, Article, DNA sequencing, 03 medical and health sciences, 030104 developmental biology, Genetic marker, Medicine, 1000 Genomes Project, Indel, Allele frequency, Imputation (genetics)
Abstract

Genotype imputation is a powerful strategy for achieving the large sample sizes required for identification of variants underlying complex phenotypes, but imputation of rare variants remains problematic. Genetically isolated populations offer one solution, however population-specific reference panels are needed to assure optimal imputation accuracy and allele frequency estimation. Here we report the Anabaptist Genome Reference Panel (AGRP), the first whole-genome catalogue of variants and phased haplotypes in people of Amish and Mennonite ancestry. Based on high-depth whole-genome sequence (WGS) from 265 individuals, the AGRP contains >12 M high-confidence single nucleotide variants and short indels, of which ~12.5% are novel. These Anabaptist-specific variants were more deleterious than variants with comparable frequencies observed in the 1000 Genomes panel. About 43,000 variants showed enriched allele frequencies in AGRP, consistent with drift. When combined with the 1000 Genomes Project reference panel, the AGRP substantially improved imputation, especially for rarer variants. The AGRP is freely available to researchers through an imputation server.

Published
2017

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